Plane wave analysis of rectangular axial-inlet, axial-outlet and transverse-inlet, transverse-outlet air cleaners

In this work, one-dimensional flow-acoustic analysis of two basic configurations of air cleaners, (i) Rectangular Axial-Inlet, Axial-Outlet (RAIAO) and (ii) Rectangular Transverse-Inlet, Transverse-Outlet (RTITO), has been presented. This 1-D analytical approach has been verified with the help of 3-D FEM based software. Through subtraction of the acoustic performance of the bare plenum (without filter element) from that of the complete air cleaner box, the solitary performance of the filter element has been evaluated. Part of the present analysis illustrates that the analytical formulation remains effective even with offset positioning of the air pipes from the centre of the cross section of the air cleaner. The 1-D analytical tool computes much faster than its 3-D simulation counterpart. The present analysis not only predicts the acoustical impact of mean flow, but it also depicts the scenario with increased resistance of the filter element. Thus, the proposed 1-D analysis would help in the design of acoustically efficient air cleaners for automotive applications. (C) 2011 Institute of Noise Control Engineering.

Acoustical behavior of single inlet and multiple outlet elliptical cylindrical chamber muffler

Transmission loss (TL) of an elliptical cylindrical chamber muffler having a single side/end inlet and multiple side/end outlet is analyzed by means of the 3-D semi-analytical formulation based upon the modal expansion (in terms of the angular and radial Mathieu functions) and the Green's function. The acoustic pressure response obtained in terms of Green's function is integrated over surface area of the side/end ports (modeled as rigid pistons) and upon subsequent division by the port area, yields the acoustic pressure response or impedance Z] matrix parameters due to the uniform piston-driven model. The 3-D semi-analytical results are found to be in excellent agreement with the results obtained by means of 3-D FEA (SYSNOISE) simulations, thereby validating the semi-analytical procedure suggested in this work. Parametric studies such as the effect of chamber length (L), angular and axial locations of the ports, interchanging the locations of inlet and outlet ports as well as the addition of an outlet port for double outlet mufflers on the TL performance are reported, thereby leading to the formulation of design guidelines for obtaining muffler configurations exhibiting a broad-band TL spectrum. One such configuration is an axially long chamber having side-inlet and side-outlet ports such that one of the side ports is located at half the axial length on themajor/minor axis and the other side port is located at three-quarters (or one-quarter) of the axial length on the minor/major axis. (C) 2012 Institute of Noise Control Engineering.

A novel Q-learning algorithm with function approximation for constrained Markov decision processes

We present a novel multi-timescale Q-learning algorithm for average cost control in a Markov decision process subject to multiple inequality constraints. We formulate a relaxed version of this problem through the Lagrange multiplier method. Our algorithm is different from Q-learning in that it updates two parameters - a Q-value parameter and a policy parameter. The Q-value parameter is updated on a slower time scale as compared to the policy parameter. Whereas Q-learning with function approximation can diverge in some cases, our algorithm is seen to be convergent as a result of the aforementioned timescale separation. We show the results of experiments on a problem of constrained routing in a multistage queueing network. Our algorithm is seen to exhibit good performance and the various inequality constraints are seen to be satisfied upon convergence of the algorithm.

Improved tuning of the extended concentric tube resonator for wide-band transmission loss

Transmission loss (TL) of a simple expansion chamber (SEC) consists of periodic domes with sharp troughs. This limits practical application of the SEC in the variable-speed automobile exhaust systems. Three-fourths of the troughs of the SEC can be lifted by appropriate tuning of the extended inlet/outlet lengths. However, such mufflers suffer from high back pressure and generation of aerodynamic noise due to free shear layers at the area discontinuities. Therefore, a perforate bridge is made between the extended inlet and outlet. It is shown that the TL curve of a concentric tube resonator (CTR) can also be lifted in a similar way by proper tuning of the extended unperforated lengths. Differential lengths have to be used to correct the inlet/outlet lengths in order to account for the perforate inertance. The resonance peak frequencies calculated by means of the 1-D analysis are compared with those of the 3-D FEM, and appropriate differential lengths are calculated. It is shown how different geometric characteristics of the muffler and mean flow affect the differential lengths. A general correlation is obtained for the differential lengths by considering seven relevant geometric and environmental parameters in a comprehensive parametric study. The resulting expressions would help in design of extended-tube CTR for wide-band TL. (C) 2014 Institute of Noise Control Engineering.

Model Predictive Static Programming: A Computationally Efficient Technique For Suboptimal Control Design

Combining the philosophies of nonlinear model predictive control and approximate dynamic programming, a new suboptimal control design technique is presented in this paper, named as model predictive static programming (MPSP), which is applicable for finite-horizon nonlinear problems with terminal constraints. This technique is computationally efficient, and hence, can possibly be implemented online. The effectiveness of the proposed method is demonstrated by designing an ascent phase guidance scheme for a ballistic missile propelled by solid motors. A comparison study with a conventional gradient method shows that the MPSP solution is quite close to the optimal solution.

Ant colony optimization for reporting cell planning in mobile computing using selective paging strategy

Location management problem that arise in mobile computing networks is addressed. One method used in location management is to designate sonic of the cells in the network as "reporting cells". The other cells in the network are "non-reporting cells". Finding an optimal set of reporting cells (or reporting cell configuration) for a given network. is a difficult combinatorial optimization problem. In fact this is shown to be an NP-complete problem. in an earlier study. In this paper, we use the selective paging strategy and use an ant colony optimization method to obtain the best/optimal set of reporting cells for a given a network.

Joint Power Control, Scheduling and Routing for Multihop Energy Harvesting Sensor Networks

We study wireless multihop energy harvesting sensor networks employed for random field estimation. The sensors sense the random field and generate data that is to be sent to a fusion node for estimation. Each sensor has an energy harvesting source and can operate in two modes: Wake and Sleep. We consider the problem of obtaining jointly optimal power control, routing and scheduling policies that ensure a fair utilization of network resources. This problem has a high computational complexity. Therefore, we develop a computationally efficient suboptimal approach to obtain good solutions to this problem. We study the optimal solution and performance of the suboptimal approach through some numerical examples.

Parallel computing concepts and methods for floquet analysis of helicopter trim and stability

Floquet analysis is widely used for small-order systems (say, order M < 100) to find trim results of control inputs and periodic responses, and stability results of damping levels and frequencies, Presently, however, it is practical neither for design applications nor for comprehensive analysis models that lead to large systems (M > 100); the run time on a sequential computer is simply prohibitive, Accordingly, a massively parallel Floquet analysis is developed with emphasis on large systems, and it is implemented on two SIMD or single-instruction, multiple-data computers with 4096 and 8192 processors, The focus of this development is a parallel shooting method with damped Newton iteration to generate trim results; the Floquet transition matrix (FTM) comes out as a byproduct, The eigenvalues and eigenvectors of the FTM are computed by a parallel QR method, and thereby stability results are generated, For illustration, flap and flap-lag stability of isolated rotors are treated by the parallel analysis and by a corresponding sequential analysis with the conventional shooting and QR methods; linear quasisteady airfoil aerodynamics and a finite-state three-dimensional wake model are used, Computational reliability is quantified by the condition numbers of the Jacobian matrices in Newton iteration, the condition numbers of the eigenvalues and the residual errors of the eigenpairs, and reliability figures are comparable in both the parallel and sequential analyses, Compared to the sequential analysis, the parallel analysis reduces the run time of large systems dramatically, and the reduction increases with increasing system order; this finding offers considerable promise for design and comprehensive-analysis applications.

Model-following Neuro-adaptive approach for robust control of high performance aircrafts

Based on dynamic inversion, a relatively straightforward approach is presented in this paper for nonlinear flight control design of high performance aircrafts, which does not require the normal and lateral acceleration commands to be first transferred to body rates before computing the required control inputs. This leads to substantial improvement of the tracking response. Promising results are obtained from six degree-offreedom simulation studies of F-16 aircraft, which are found to be superior as compared to an existing approach (which is also based on dynamic inversion). The new approach has two potential benefits, namely reduced oscillatory response (including elimination of non-minimum phase behavior) and reduced control magnitude. Next, a model-following neuron-adaptive design is augmented the nominal design in order to assure robust performance in the presence of parameter inaccuracies in the model. Note that in the approach the model update takes place adaptively online and hence it is philosophically similar to indirect adaptive control. However, unlike a typical indirect adaptive control approach, there is no need to update the individual parameters explicitly. Instead the inaccuracy in the system output dynamics is captured directly and then used in modifying the control. This leads to faster adaptation, which helps in stabilizing the unstable plant quicker. The robustness study from a large number of simulations shows that the adaptive design has good amount of robustness with respect to the expected parameter inaccuracies in the model.

Optimal Hop Distance and Power Control for a Single Cell, Dense, Ad Hoc Wireless Network

We consider a dense, ad hoc wireless network, confined to a small region. The wireless network is operated as a single cell, i.e., only one successful transmission is supported at a time. Data packets are sent between source-destination pairs by multihop relaying. We assume that nodes self-organize into a multihop network such that all hops are of length d meters, where d is a design parameter. There is a contention-based multiaccess scheme, and it is assumed that every node always has data to send, either originated from it or a transit packet (saturation assumption). In this scenario, we seek to maximize a measure of the transport capacity of the network (measured in bit-meters per second) over power controls (in a fading environment) and over the hop distance d, subject to an average power constraint. We first motivate that for a dense collection of nodes confined to a small region, single cell operation is efficient for single user decoding transceivers. Then, operating the dense ad hoc wireless network (described above) as a single cell, we study the hop length and power control that maximizes the transport capacity for a given network power constraint. More specifically, for a fading channel and for a fixed transmission time strategy (akin to the IEEE 802.11 TXOP), we find that there exists an intrinsic aggregate bit rate (Theta(opt) bits per second, depending on the contention mechanism and the channel fading characteristics) carried by the network, when operating at the optimal hop length and power control. The optimal transport capacity is of the form d(opt)((P) over bar (t)) x Theta(opt) with d(opt) scaling as (P) over bar (t) (1/eta), where (P) over bar (t) is the available time average transmit power and eta is the path loss exponent. Under certain conditions on the fading distribution, we then provide a simple characterization of the optimal operating point. Simulation results are provided comparing the performance of the optimal strategy derived here with some simple strategies for operating the network.

ELISA: An Estimated Load Information Scheduling Algorithm for Distributed Computing Systems

In this paper, we present a decentralized dynamic load scheduling/balancing algorithm called ELISA (Estimated Load Information Scheduling Algorithm) for general purpose distributed computing systems. ELISA uses estimated state information based upon periodic exchange of exact state information between neighbouring nodes to perform load scheduling. The primary objective of the algorithm is to cut down on the communication and load transfer overheads by minimizing the frequency of status exchange and by restricting the load transfer and status exchange within the buddy set of a processor. It is shown that the resulting algorithm performs almost as well as a perfect information algorithm and is superior to other load balancing schemes based on the random sharing and Ni-Hwang algorithms. A sensitivity analysis to study the effect of various design parameters on the effectiveness of load balancing is also carried out. Finally, the algorithm's performance is tested on large dimensional hypercubes in the presence of time-varying load arrival process and is shown to perform well in comparison to other algorithms. This makes ELISA a viable and implementable load balancing algorithm for use in general purpose distributed computing systems.

Mechanical processing and microstructural control in hot working of hot isostatically pressed P/M IN-100 superalloy

The hot deformation behavior of hot isostatically pressed (HIPd) P/M IN-100 superalloy has been studied in the temperature range 1000-1200 degrees C and strain rate range 0.0003-10 s(-1) using hot compression testing. A processing map has been developed on the basis of these data and using the principles of dynamic materials modelling. The map exhibited three domains: one at 1050 degrees C and 0.01 s(-1), with a peak efficiency of power dissipation of approximate to 32%, the second at 1150 degrees C and 10 s(-1), with a peak efficiency of approximate to 36% and the third at 1200 degrees C and 0.1 s(-1), with a similar efficiency. On the basis of optical and electron microscopic observations, the first domain was interpreted to represent dynamic recovery of the gamma phase, the second domain represents dynamic recrystallization (DRX) of gamma in the presence of softer gamma', while the third domain represents DRX of the gamma phase only. The gamma' phase is stable upto 1150 degrees C, gets deformed below this temperature and the chunky gamma' accumulates dislocations, which at larger strains cause cracking of this phase. At temperatures lower than 1080 degrees C and strain rates higher than 0.1 s(-1), the material exhibits flow instability, manifested in the form of adiabatic shear bands. The material may be subjected to mechanical processing without cracking or instabilities at 1200 degrees C and 0.1 s(-1), which are the conditions for DRX of the gamma phase.

Implementation of Art1 and Art2 Artificial Neural Networks on Ring and Mesh Architectures

The Artificial Neural Networks (ANNs) are being used to solve a variety of problems in pattern recognition, robotic control, VLSI CAD and other areas. In most of these applications, a speedy response from the ANNs is imperative. However, ANNs comprise a large number of artificial neurons, and a massive interconnection network among them. Hence, implementation of these ANNs involves execution of computer-intensive operations. The usage of multiprocessor systems therefore becomes necessary. In this article, we have presented the implementation of ART1 and ART2 ANNs on ring and mesh architectures. The overall system design and implementation aspects are presented. The performance of the algorithm on ring, 2-dimensional mesh and n-dimensional mesh topologies is presented. The parallel algorithm presented for implementation of ART1 is not specific to any particular architecture. The parallel algorithm for ARTE is more suitable for a ring architecture.